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Open AccessArticle

Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging

1
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
2
Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Christian Huck
Molecules 2019, 24(12), 2227; https://doi.org/10.3390/molecules24122227
Received: 31 May 2019 / Accepted: 13 June 2019 / Published: 14 June 2019
Seed vitality is one of the primary determinants of high yield that directly affects the performance of seedling emergence and plant growth. However, seed vitality may be lost during storage because of unfavorable conditions, such as high moisture content and temperatures. It is therefore vital for seed companies as well as farmers to test and determine seed vitality to avoid losses of any kind before sowing. In this study, near-infrared hyperspectral imaging (NIR-HSI) combined with multiple data preprocessing methods and classification models was applied to identify the vitality of rice seeds. A total of 2400 seeds of three different years: 2015, 2016 and 2017, were evaluated. The experimental results show that the NIR-HSI technique has great potential for identifying vitality and vigor of rice seeds. When detecting the seed vitality of the three different years, the extreme learning machine model with Savitzky–Golay preprocessing could achieve a high classification accuracy of 93.67% by spectral data from only eight wavebands (992, 1012, 1119, 1167, 1305, 1402, 1629 and 1649 nm), which could be developed for a fast and cost-effective seed-sorting system for industrial online application. When identifying non-viable seeds from viable seeds of different years, the least squares support vector machine model coupled with raw data and selected wavelengths of 968, 988, 1204, 1301, 1409, 1463, 1629, 1646 and 1659 nm achieved better classification performance (94.38% accuracy), and could be adopted as an optimal combination to identify non-viable seeds from viable seeds. View Full-Text
Keywords: seeds vitality; rice seeds; near-infrared spectroscopy; hyperspectral image; discriminant analysis seeds vitality; rice seeds; near-infrared spectroscopy; hyperspectral image; discriminant analysis
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MDPI and ACS Style

He, X.; Feng, X.; Sun, D.; Liu, F.; Bao, Y.; He, Y. Rapid and Nondestructive Measurement of Rice Seed Vitality of Different Years Using Near-Infrared Hyperspectral Imaging. Molecules 2019, 24, 2227.

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